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| -rw-r--r-- | benchmarks/README.rst | 35 |
1 files changed, 33 insertions, 2 deletions
diff --git a/benchmarks/README.rst b/benchmarks/README.rst index 2700e95e7..135527e4f 100644 --- a/benchmarks/README.rst +++ b/benchmarks/README.rst @@ -22,8 +22,8 @@ By default, `asv` ships with support for anaconda and virtualenv:: pip install asv pip install virtualenv -After contributing new benchmarks, you should test them locally -before submitting a pull request. +After contributing new benchmarks, you should test them locally before +submitting a pull request. To run all benchmarks, navigate to the root NumPy directory at the command line and execute:: @@ -36,6 +36,16 @@ defined in ``benchmarks/``. (Note: this could take a while. Each benchmark is run multiple times to measure the distribution in execution times.) +For **testing** benchmarks locally, it may be better to run these without +replications:: + + cd benchmarks/ + export REGEXP="bench.*Ufunc" + asv run --dry-run --show-stderr --python=same --quick -b $REGEXP + +Where the regular expression used to match benchmarks is stored in ``$REGEXP``, +and `--quick` is used to avoid repetitions. + To run benchmarks from a particular benchmark module, such as ``bench_core.py``, simply append the filename without the extension:: @@ -69,6 +79,27 @@ Command-line help is available as usual via ``asv --help`` and .. _ASV documentation: https://asv.readthedocs.io/ +Benchmarking versions +--------------------- + +To benchmark or visualize only releases on different machines locally, the tags with their commits can be generated, before being run with ``asv``, that is:: + + cd benchmarks + # Get commits for tags + # delete tag_commits.txt before re-runs + for gtag in $(git tag --list --sort taggerdate | grep "^v"); do + git log $gtag --oneline -n1 --decorate=no | awk '{print $1;}' >> tag_commits.txt + done + # Use the last 20 + tail --lines=20 tag_commits.txt > 20_vers.txt + asv run HASHFILE:20_vers.txt + # Publish and view + asv publish + asv preview + +For details on contributing these, see the `benchmark results repository`_. + +.. _benchmark results repository: https://github.com/HaoZeke/asv-numpy Writing benchmarks ------------------ |